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WO2018012770A1 - Procédé et système de gestion d'exercices utilisant un capteur d'électromyographie - Google Patents

Procédé et système de gestion d'exercices utilisant un capteur d'électromyographie Download PDF

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Publication number
WO2018012770A1
WO2018012770A1 PCT/KR2017/006897 KR2017006897W WO2018012770A1 WO 2018012770 A1 WO2018012770 A1 WO 2018012770A1 KR 2017006897 W KR2017006897 W KR 2017006897W WO 2018012770 A1 WO2018012770 A1 WO 2018012770A1
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WIPO (PCT)
Prior art keywords
exercise
muscle
monitoring module
emg sensor
activity
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Ceased
Application number
PCT/KR2017/006897
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English (en)
Korean (ko)
Inventor
한형섭
송경영
권오국
김태영
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Hhs Co ltd
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Hhs Co ltd
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Priority to CN201780046000.7A priority Critical patent/CN109716443B/zh
Priority to US16/317,525 priority patent/US20210330211A1/en
Publication of WO2018012770A1 publication Critical patent/WO2018012770A1/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q20/00—Payment architectures, schemes or protocols
    • G06Q20/30—Payment architectures, schemes or protocols characterised by the use of specific devices or networks
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A61B5/389—Electromyography [EMG]
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A61B5/389—Electromyography [EMG]
    • A61B5/397—Analysis of electromyograms
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235—Details of waveform analysis
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7271—Specific aspects of physiological measurement analysis
    • A—HUMAN NECESSITIES
    • A63—SPORTS; GAMES; AMUSEMENTS
    • A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
    • A63B24/00—Electric or electronic controls for exercising apparatus of preceding groups; Controlling or monitoring of exercises, sportive games, training or athletic performances
    • A63B24/0062—Monitoring athletic performances, e.g. for determining the work of a user on an exercise apparatus, the completed jogging or cycling distance
    • G—PHYSICS
    • G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
    • G09B19/00—Teaching not covered by other main groups of this subclass
    • G09B19/003—Repetitive work cycles; Sequence of movements
    • G09B19/0038—Sports
    • G—PHYSICS
    • G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
    • G09B5/00—Electrically-operated educational appliances
    • G09B5/02—Electrically-operated educational appliances with visual presentation of the material to be studied, e.g. using film strip
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
    • G16H20/30—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
    • G16H40/60—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices
    • G16H40/67—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for remote operation
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B2503/00—Evaluating a particular growth phase or type of persons or animals
    • A61B2503/10—Athletes
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/0002—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network
    • A61B5/0015—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network characterised by features of the telemetry system
    • A61B5/0022—Monitoring a patient using a global network, e.g. telephone networks, internet
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/25—Bioelectric electrodes therefor
    • A61B5/251—Means for maintaining electrode contact with the body
    • A61B5/256—Wearable electrodes, e.g. having straps or bands
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235—Details of waveform analysis
    • A61B5/7246—Details of waveform analysis using correlation, e.g. template matching or determination of similarity
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks

Definitions

  • the present invention relates to an exercise management method and system using an EMG sensor, and more particularly, to an exercise management method and system using a wearable EMG sensor.
  • Korean Patent Laid-Open Publication No. 10-2014-0113125 discloses a technology for providing a personalized exercise management method to a mobile terminal.
  • An object of the present invention to provide a method and system for managing exercise using a wearable EMG sensor.
  • the embodiment is connected to a monitoring module in which an exercise management application is installed and a wired / wireless communication network to receive exercise information, provide a control server for providing analysis information of a user's exercise, and a plurality of EMGs attached to a user's body. It provides a motion management system using an EMG sensor that receives a detection signal from a sensor, analyzes the detection signal to calculate muscle activity, and provides a signal processing module to the monitoring module.
  • the signal processing module may include a signal analyzer configured to analyze the detection signal and select an intrinsic mode function (IMF) and a maximum change rate subband above a threshold value, and a feature extractor that calculates muscle activity from the IMF and the maximum change rate subband. It may include.
  • IMF intrinsic mode function
  • a feature extractor that calculates muscle activity from the IMF and the maximum change rate subband. It may include.
  • the activity of the muscle may be calculated by the degree of muscle contractility, muscle fatigue, muscle contraction timing.
  • the muscle contraction muscle tone is calculated from the RMS of the IMF and the maximum change rate subband, the fatigue of the muscle is calculated from the median frequency, and the muscle contraction timing can be calculated from the cross-correlation function between the plurality of EMG sensors. have.
  • the embodiment is a method of performing exercise management through the exercise management application of a plurality of EMG sensors and monitoring module, receiving the exercise information in conjunction with the wired / wireless communication network from the monitoring module, and from the EMG sensor Receiving the attachment position information of the EMG sensor, receiving each detection signal from the EMG sensor when the exercise is started, analyzing the detection signal to calculate muscle activity, and providing the monitoring module to the monitoring module, and By analyzing the exercise information and the activity of the muscle to derive an improvement method, and providing the exercise management method comprising the step of feeding back the improvement method to the monitoring module.
  • the calculating of the activity of the muscle may include analyzing the detection signal to select an intrinsic mode function (IMF) and a maximum change rate subband above a threshold value, selecting the IMF and the maximum change rate subband, and the IMF and Calculating the muscle contraction muscle tension from the RMS of the maximum change rate subband, calculating the fatigue level of the muscle from the median frequency, and calculating the muscle contraction timing from the cross-correlation function between channels to provide the muscle activity.
  • IMF intrinsic mode function
  • Embodiments can reduce the cost burden of personal training and improve the monotony of the exercise alone.
  • FIG. 1 is a block diagram of an entire system including an exercise management system using an EMG sensor according to an embodiment of the present invention.
  • FIG. 2 is a diagram illustrating the entire system of FIG. 1.
  • 3 is a detailed configuration diagram of the EMG sensor.
  • FIG. 4 is a detailed configuration diagram of a signal processing module.
  • FIG. 5 is a flow chart showing the operation of the entire system of FIG.
  • FIG. 6 is a detailed flowchart illustrating a process of calculating muscle activity of the signal processing module of FIG. 5.
  • FIG. 1 is a configuration diagram of an entire system including an exercise management system using an EMG sensor according to an embodiment of the present invention
  • FIG. 2 is a diagram illustrating the entire system of FIG. 1
  • FIG. 3 is a detailed configuration of an EMG sensor.
  • 4 is a detailed configuration diagram of a signal processing module.
  • exercise management server 500 using the EMG sensor according to an embodiment of the present invention monitoring module 300, Exercise management server 500, EMG sensor 100 and a plurality of exercise equipment (not shown) is included.
  • the monitoring module 300 is a terminal on which a user can download and install an exercise management application from the exercise management server 100 by accessing the exercise management server 500.
  • the monitoring module 300 includes a smartphone, a laptop or a tablet PC including a display window. Include.
  • the monitoring module 300 is interlocked with the exercise management server 500 through a wired or wireless Internet, wherein the wireless Internet may be wifi, Bluetooth and the like.
  • the monitoring module 300 installs an exercise management application for the exercise management server 500, drives the application to transmit various information to the exercise management server 500, and receives various information from the exercise management server 500. can do.
  • the EMG sensor 100 includes a plurality of sensor modules 110, and each sensor module 110 is implemented as a wearable device.
  • each EMG sensor module 110 is formed in a band-type structure is formed to be directly attached to the user's body.
  • the EMG sensor module 110 may transmit a detection signal by sensing the EMG of the movement according to the exercise of the user.
  • the EMG sensor module 110 is provided with a communication unit 115 for wireless communication with the signal processing module 200 to transmit a detection signal generated according to the user's movement to the signal processing module 200.
  • the plurality of sensor modules 110 of the EMG sensor 200 may be attached to various body parts of the user and simultaneously transmit respective detection signals.
  • the user may freely attach the user's arm, leg, chest, and buttocks to the user, and the user may attach to a target muscle position during exercise to detect an exercise effect on the target muscle.
  • Each EMG sensor module 110 has a unique serial number, and the serial number is transmitted to the signal processing module 200 together with the generated detection signal to the respective sensor module 110 in the signal processing module 200. ) Can be identified.
  • Each EMG sensor module 110 may have a detailed configuration as shown in FIG. 3.
  • each EMG sensor module 110 may include a sensor unit 111, an A / D converter 113, a communication unit 115, and a battery 117.
  • the sensor unit 111 measures the surface EMG by sensing the biosignal accompanying the activity of the muscle detected through the electrode attached around the muscle as an EMG sensor.
  • the EMG sensor attaches two electrodes, a reference electrode and a measurement electrode, to the human body to measure the amount of voltage, current, and frequency flowing around the muscle.
  • the potential difference formed between the two electrodes is amplified by the amplifier of the sensor, the power supply noise of 60Hz can be removed by the filter.
  • the low-pass filter detects EMG signals by removing noise from high-frequency components.
  • the A / D converter 113 digitizes and outputs the EMG signal of the sensor unit 111, and the communication unit 115 transmits the digital signal to the signal processing module through a wired or wireless communication network, wherein the communication unit 115 Transmits each EMG sensor serial number together.
  • the EMG sensor module 110 may each include a battery 117, and the battery 117 may be a rechargeable battery 117.
  • the exercise management server 500 may include a signal processing module 200 and a control server 400 as shown in FIG. 1, and the signal processing module 200 and the control server 400 may be physically separated from each other. But can be functionally separated from one PC.
  • the signal processing module 200 receives various sensing signals from the EMG sensor 100 through a wired or wireless communication network, and processes and reads them to calculate muscle activity, which is a valid feature value.
  • the signal processing module 200 may include a synchronization and filtering unit 210, a signal analyzer 220, and a feature extractor 230.
  • the synchronization and filtering unit 210 synchronizes a plurality of detection signals received from the respective EMG sensor modules 110 for each channel and performs noise filtering.
  • the signal analyzer 220 includes a first analyzer 221 and a second analyzer 223 for obtaining a valid feature value from the sensed signal.
  • the first analyzer 221 decomposes the filtered detection signal by using EMD (empirical mode decomposition) into a plurality of intrinsic mode functions (IMFs), obtains spectral values for each IMF, and thresholds from harmonic characteristics and power ratios.
  • EMD empirical mode decomposition
  • IMFs intrinsic mode functions
  • the second analyzing unit 223 decomposes the filtered detection signal by using a discrete wavelet transform (DWT) into a plurality of subbands, obtains an average, variance, skewness, and kurtosis of each band, and obtains each subband for each frame. You can select the maximum rate of change subband that has the largest rate of change of the value.
  • DWT discrete wavelet transform
  • the IMFs value and the maximum rate of change subband are defined as valid feature values.
  • the feature extractor 230 calculates muscle activity from the selected valid feature value. Specifically, RMS is calculated from selected IMFs and selected subbands to calculate muscle contractile muscle tone and muscle fatigue from median frequency. In addition, the feature extractor 230 analyzes muscle contraction timing by using cross-correlation between channels.
  • the feature extractor 230 may extract muscle contraction tension, fatigue, and muscle contraction timing to transmit muscle activity.
  • control server 400 checks whether the user is a member of the exercise management service through a wired or wireless communication network, and if the user is a member of the exercise management service, receives the physical information and exercise information of the exercise management service subscriber, and analyzes and customizes it.
  • An exercise program can be proposed and an improvement method for the current exercise method can be provided.
  • the exercise management server 500 including the signal processing module 200 and the control server 400 may be installed in the monitoring module 300 to display improvement methods and feedback during such exercise, and each EMG sensor module Provides an exercise management application that can send start information and the like to 110.
  • the exercise management system 500 is a state in which the user installs the exercise management application on the monitoring module 300, for example, the user's smartphone, and attaches the plurality of EMG sensor modules 110 to the part of the body to be exercised. Perform the action in.
  • FIG. 5 is a flowchart illustrating an operation of the entire system of FIG. 1, and FIG. 6 is a detailed flowchart illustrating a process of calculating muscle activity of the signal processing module of FIG. 5.
  • the user selects the exercise operation in the state of having a monitoring module 300 installed with an exercise management application, for example, a smartphone, and if there is an exercise device to be used (S100). If a separate device is not needed, selection of the exercise device may be omitted.
  • an exercise management application for example, a smartphone
  • the user drives the exercise management application of the smartphone to describe the current exercise time and the physiological state of the user exercising (S110).
  • the physiological state may be gender, height, weight, age, abdominal obesity, etc.
  • the physiological state information may be measured through various measuring instruments, for example, a weight scale, a tape measure, an inbody, and the like.
  • the body information may be transmitted to the exercise management server 500 through a wired / wireless communication network.
  • the exercise management server 500 requests attachment position information of each sensor unit 111 of the sensor module 110 from the EMG sensor 100 and receives corresponding position information (S120). At this time, the location information is also transmitted to the monitoring module 300.
  • the monitoring module 300 When the monitoring module 300 receives the location information, the monitoring module 300 initializes the device and starts the exercise (S130).
  • the monitoring module 300 may transmit the corresponding exercise information, that is, time, device, physiological state, etc. to the exercise management server 500 through the application (S140).
  • the EMG sensor 100 When the exercise is started, the EMG sensor 100 generates a detection signal and transmits it to the signal processing module 200 of the exercise management server 500 (S150).
  • the signal processing module 200 calculates the muscle activity for each operation from the detection signal and transmits it to the monitoring module 300 (S160).
  • a sensing signal is received, and the sensing signal is decomposed into several intrinsic mode functions (IMFs) using EMD (empirical mode decomposition) (S161).
  • IMFs intrinsic mode functions
  • the spectral values of the respective IMFs of the corresponding IMFs are obtained and selected as IMFs when the threshold value is greater than the threshold value from the harmonic characteristics and the power ratio (S162).
  • the filtered detection signal is decomposed into a plurality of subbands using a discrete wavelet transform (DWT) (S164).
  • DWT discrete wavelet transform
  • the average, variance, skewness, and kurtosis of each band are obtained to select the maximum change rate subband having the largest change rate among the change rates of the values obtained in each subband for each frame (S165).
  • the IMFs value and the maximum change rate subband are defined as valid feature values, and the activity of the muscle is calculated from the effective feature values (S166). Specifically, RMS is calculated from selected IMFs and selected subbands to calculate muscle contractile muscle tone and muscle fatigue from median frequency.
  • muscle contraction timing is analyzed using a cross-correlation between channels, that is, between each sensor module 110 (S167).
  • the muscle contraction muscle tension degree, fatigue degree, muscle contraction timing is extracted and transmitted to the monitoring module 300 as the activity of the muscle.
  • the monitoring module 300 receives the activity of the muscle and displays it (S170).
  • the activity through the exercise management application is displayed in the form of a body map (body map) to be easily and effectively recognized by the user.
  • control server 400 of the exercise management server 500 analyzes the muscle activity and exercise information from the signal processing module 200 to determine the exercise state of the user and derive a method of improving the exercise state. To the monitoring module 300.
  • the monitoring module 300 receives this through the application, displays it as an exercise prescription, feeds back to the user, and terminates the application.
  • the control server 400 updates the database by archive analysis including the exercise prescription.
  • the wearable EMG sensor is attached to the user's exercise site and the exercise activity is read and shown in real time as the exercise progresses, thereby providing the accuracy and improvement of the exercise, thereby enabling efficient exercise.

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Abstract

La présente invention concerne un système de gestion d'exercices utilisant un capteur d'électromyographie, comprenant : un serveur de commande pour recevoir des informations d'exercices en interagissant avec un module de surveillance ayant une application de gestion d'exercices installée dans celui-ci, par l'intermédiaire d'un réseau de communication câblé/sans fil et fournissant des informations d'analyse concernant un exercice d'un utilisateur; et un module de traitement de signal destiné à recevoir un signal de détection provenant d'une pluralité de capteurs d'électromyographie fixés au corps de l'utilisateur, analysant le signal détecté afin de calculer une activité musculaire et à fournir l'activité musculaire calculée au module de surveillance. Par conséquent, le mode de réalisation de la présente invention peut réduire la charge de coût de l'entraînement personnel et améliorer la monotonie de s'entraîner seul. En outre, il n'y a pas de restriction sur un lieu et un temps puisque l'exercice peut être effectué ailleurs que dans une zone d'exercice limitée. En outre, un utilisateur peut s'exercer efficacement en visualisant sa propre quantité d'exercice et l'utilisation du muscle et analogue, en connectant un capteur d'électromyographie à un smartphone.
PCT/KR2017/006897 2016-07-12 2017-06-29 Procédé et système de gestion d'exercices utilisant un capteur d'électromyographie Ceased WO2018012770A1 (fr)

Priority Applications (2)

Application Number Priority Date Filing Date Title
CN201780046000.7A CN109716443B (zh) 2016-07-12 2017-06-29 利用肌电图传感器的运动管理方法以及系统
US16/317,525 US20210330211A1 (en) 2016-07-12 2017-06-29 Exercise management method and system using electromyography sensor

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
KR10-2016-0088023 2016-07-12
KR1020160088023A KR101845323B1 (ko) 2016-07-12 2016-07-12 근전도 센서를 이용한 운동 관리 방법 및 시스템

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US (1) US20210330211A1 (fr)
KR (1) KR101845323B1 (fr)
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WO (1) WO2018012770A1 (fr)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108606790A (zh) * 2018-04-03 2018-10-02 厦门攸信信息技术有限公司 一种肌肉均匀运动指导方法及系统

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